》  Research Fields

Artificial intelligence, machine learning, data mining, VLA embodied multimodal large models, 3D generation

》  Courses

Machine Learning, The Frontiers of Robotics and Artificial Intelligence, Pattern Recognition

》  Projects

Research on the Representational Power of Graph Neural Networks, 570,000¥, National Natural Science Foundation of China (NSFC), 2022/01-2025/12, Principal Investigator.

》  Publications

1. Bootstrap Deep Spectral Clustering with Optimal Transport, Wengang Guo, Wei Ye*, Chunchun Chen, Xin Sun, Christian Böhm, Claudia Plant, Susanto Rahardja, IEEE Transactions on Multimedia (TMM), 2025.

2. Deep Hierarchical Graph Alignment Kernels, Shuhao Tang, Hao Tian, Xiaofeng Cao, Wei Ye*, International Joint Conference on Artificial Intelligence (IJCAI), 2024.

3. PICNN: A Pathway towards Interpretable Convolutional Neural Networks, Wengang Guo, Jiayi Yang, Huilin Yin, Qijun Chen, Wei Ye*, AAAI Conference on Artificial Intelligence (AAAI), 2024.

4. COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems, Hao Tian, Sourav Medya, Wei Ye*, AAAI Conference on Artificial Intelligence (AAAI), 2024.

5. Learning Deep Graph Representations via Convolutional Neural Networks, Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.